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Estimation and Improvement of Routing Protocol Mobile Ad-Hoc Network Using Fuzzy Neural Network
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Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one protocol to another depending on the applications used in the network. The network design is done using the program (Op-Net V14.5 modular) with core i7 computer for multiple nodes deployed randomly in several area (100 * 100, 200 * 200, 400 * 400, 800 * 800, 1000 * 1000)m2 accomplished by changing the number of nodes in the network (10, 20, 40 and 80). There are three programs designed using (MATLAB 2012A programming language). The first one evaluates the (QoS) using the organizational structure of the mysterious system (HFS), which relied on the standard applications that should be provided by the protocols to make the applications accepted by the nodes requirements. After the evaluation the QoS for all cases, we design Neural Network to assist in estimation of the best protocol for any network through QoS for all protocols (AODV, DSR, OLSR and TORA). Neural network has four entrances (area, number of nodes, real time application ratio and non-real time application ratio). The results show that the QoS estimated is (0.5401) of (OLSR) which has been improved to (0.6421) by reducing to mobility speed and making some nodes fixed and using more than one protocol in  the network to provide the best QoS .

 

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Publication Date
Sat Jan 18 2025
Journal Name
Cell Biochemistry And Biophysics
Histone Deacetylation in Alzheimer’s Diseases (AD); Hope or Hype
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Scopus (2)
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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Properties of Fuzzy Compact Linear Operators on Fuzzy Normed Spaces
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In this paper the definition of fuzzy normed space is recalled and its basic properties. Then the definition of fuzzy compact operator from fuzzy normed space into another fuzzy normed space is introduced after that the proof of an operator is fuzzy compact if and only if the image of any fuzzy bounded sequence contains a convergent subsequence is given. At this point the basic properties of the vector space FC(V,U)of all fuzzy compact linear operators are investigated such as when U is complete and the sequence ( ) of fuzzy compact operators converges to an operator T then T must be fuzzy compact. Furthermore we see that when T is a fuzzy compact operator and S is a fuzzy bounded operator then the composition TS and ST are fuzzy compact

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Publication Date
Thu Mar 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks
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Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

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Publication Date
Thu Nov 04 2021
Journal Name
Nat. Volatiles & Essent. Oils
Using The Aqueous Extract Of Allium Sativum In Improvement Of Some Physiological And Immunological Parameter In Albino Rats
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The current study was designated to investigate the effect ofAllium sativumon some physiological and immunological parameters in rats. thirty adult rats were divided into three groups (10 rat for each). G1: served as healthy control, G2 :rats were treated with 150 mg\kg of Allium sativum, G3: treated with 300 mg\kg of Allium sativum. All treated animals were givenorally for 30 days. The aspartate , ) ALT ( alanine transaminase on some parameters were investigated such as garlic effects of total and differential counts of white blood , ) LDH ( lactate dehydrogenase ), AST ( transaminase cells(WBC) like Lymphocyte, Monocyte, Neutrophil, Basophil, Eosinophil,as

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Engineering
Effect of Repeated Earthquakes on Al-Adhaim Earth Dam Factor of Safety and Seismic Improvement Using Stone Columns
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Earth dams in regions with moderate to high seismic activity are crucial for protecting downstream communities. Iraq and its neighboring areas have seen recurrent seismic activity, notably the 2017 Halabja Earthquake, which potentially compromised the integrity of the existing earth dam. The Darbandikhan Dam, affected by an earthquake, has inadequacies in its crest and downstream slope, presenting a greater danger of significant earthquake-induced damage compared to cyclic shocks.  Consequently, evaluating the dam's safety is essential for safeguarding downstream residents and identifying optimal ways to avert slope stability failure amid recurrent seismic activity. Iraq's seismicity map is being updated to reflect earthquake magni

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Publication Date
Tue Nov 01 2016
Journal Name
2016 International Conference On Advances In Electrical, Electronic And Systems Engineering (icaees)
Efficient routing algorithm for VANETs based on distance factor
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There has been a great deal of research into the considerable challenge of managing of traffic at road junctions; its application to vehicular ad hoc network (VANET) has proved to be of great interest in the developed world. Dynamic topology is one of the vital challenges facing VANET; as a result, routing of packets to their destination successfully and efficiently is a non-simplistic undertaking. This paper presents a MDORA, an efficient and uncomplicated algorithm enabling intelligent wireless vehicular communications. MDORA is a robust routing algorithm that facilitates reliable routing through communication between vehicles. As a position-based routing technique, the MDORA algorithm, vehicles' precise locations are used to establish th

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Publication Date
Tue Jan 01 2013
Journal Name
Thesis
User Authentication Based on Keystroke Dynamics Using Artificial Neural Networks
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Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Scopus (56)
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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
New Concepts of Fuzzy Local Function: Types of fuzzy local function
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The main idea of this paper is to define other types of a fuzzy local function and study the advantages and differences between them in addition to discussing some definitions of finding new fuzzy topologies. Also in this research, a new type of fuzzy closure has been defined, where the relation between the new type and different types of fuzzy local function has been studied

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